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Record W1977522729 · doi:10.2202/1932-0191.1004

Using Imagery to Predict Self-Confidence and Anxiety in Young Elite Athletes

2006· article· en· W1977522729 on OpenAlexaffabout
Leisha Strachan, Krista J. Munroe‐Chandler

Bibliographic record

VenueJournal of Imagery Research in Sport and Physical Activity · 2006
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsAthletesAnxietyPsychologyElite athletesSelf-confidenceSomatic anxietyEliteDevelopmental psychologyClinical psychologyPhysical therapySocial psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

As elite sport participation by children increases, it is important to study the psychological development of these athletes, specifically the management of self-confidence and anxiety. Imagery is one strategy that may be used by young athletes in controlling cognitions in competition (Weiss, 1991). Although research has been conducted examining imagery use by adult athletes (Hall, 2001), there have been fewer studies investigating how imagery is related to self-confidence and anxiety in young elite athletes (c.f., Vadocz et al., 1997) hence the purpose of the current study. Female participants were recruited from baton twirling competitions in Canada and the USA. Seventy-six athletes were divided into two age cohorts: 7-11 and 12-15 years. A modified version of the Sport Imagery Questionnaire (SIQ; Hall et al., 1998) and the Competitive State Anxiety Inventory 2 for Children (CSAI-2C; Stadulis et al., 2002) were given to each participant. Results indicated that developmental differences might exist between the two age cohorts in imagery use, self-confidence, and anxiety.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.410
Teacher spread0.352 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations45
Published2006
Admission routes2
Has abstractyes

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